Chemical Risk Assessment Research Articles

A problem formulation framework for the application of in silico toxicology methods in chemical risk assessment

The first step in the hazard or risk assessment of chemicals should be to formulate the problem through a systematic and iterative process aimed at identifying and defining factors critical to the assessment. However, no general agreement exists on what components an in silico toxicology problem formulation (PF) should include. The present work aims to develop a PF framework relevant to the application of in silico models for chemical toxicity prediction. We modified and applied a PF framework from the general risk assessment literature to peer reviewed papers describing PFs associated with in silico toxicology models. Important gaps between the general risk assessment literature and the analyzed PF literature associated with in silico toxicology methods were identified. While the former emphasizes the need for PFs to address higher-level conceptual questions, the latter does not. There is also little consistency in the latter regarding the PF components addressed, reinforcing the need for a PF framework that enable users of in silico toxicology models to answer the central conceptual questions aimed at defining components critical to the model application. Using the developed framework, we highlight potential areas of uncertainty manifestation in in silico toxicology PF in instances where particular components are missing or implicitly described. The framework represents the next step in standardizing in silico toxicology PF component. The framework can also be used to improve the understanding of how uncertainty is apparent in an in silico toxicology PF, thus facilitating ways to address uncertainty.

Inconsistencies in the EU regulatory risk assessment of PFAS call for readjustment

Recognition of per- and polyfluoroalkyl substances (PFAS) as widespread environmental pollutants and a consequent risk to human health, has recently made the European Union (EU) adopt several regulatory measures for their management. The coherence of these measures is challenged by the diversity and the ubiquitous occurrence of PFAS, which also complicates the EU’s endeavor to advance justified, harmonized, and transparent approaches in the regulatory assessment of chemical risks. Our study critically reviews the European approach for the risk assessment of PFAS, by applying a comparative analysis of the current and pending regulatory thresholds issued for these chemicals in water bodies, drinking water, and certain foodstuffs. Our study shows that the level of health protection embedded in the studied thresholds may differ by three orders of magnitude, even in similar exposure settings. This is likely to confuse the common understanding of the toxicity and health risks of PFAS and undermine reasonable decision-making and the equal treatment of different stakeholders. We also indicate that currently, no consensus exists on the appropriate level of required health protection regarding PFAS and that the recently adopted tolerable intake value in the EU is too cautious. Based on our analysis, we propose some simple solutions on how the studied regulations and their implicit PFAS thresholds or their application could be improved. We further conclude that instead of setting EU-wide PFAS thresholds for all the environmental compartments, providing the member states with the flexibility to consider case-specific factors, such as regional background concentrations or food consumption rates, in their national regulatory procedures would likely result in more sustainable management of environmental PFAS without compromising the scientific foundation of risk assessment, the legitimacy of the EU policy framework and public health.

Seasonal dynamics of the standard test species Lemna sp. in outdoor microcosms.

Lemna L. sp. is a free-floating aquatic macrophyte that plays a key role as a standard test species in aquatic risk assessment for herbicides and other contaminants. Population modeling can be used to extrapolate from laboratory to field conditions. However, there are insufficient data on longer-term seasonal dynamics of this species to evaluate such models. Therefore, several long-term growth experiments were conducted in outdoor microcosms (surface area 0.174 m2). Monitoring parameters included biomass, frond numbers, water parameters, and weather data. Three different datasets were generated: frond numbers and biomass from weekly to monthly destructively sampled microcosms; a year-round dataset of frond numbers from five continuously monitored microcosms; and seasonal growth rates without the effect of density dependence over 1-2 weeks in freshly inoculated microcosms. Lemna sp. reached a maximum of approximately 500 000 fronds m-2 and 190 g dry weight m-2. During the first winter, the microcosms were covered by ice for approximately four weeks, and Lemna sp. populations collapsed. The second winter was warmer, without any ice cover, and Lemna sp. populations maintained high abundance throughout the winter. Dry weight per frond was not constant throughout the year but was highest in autumn and winter. Growth rates without density dependence under outdoor environmental conditions reached 0.29 day-1 for frond number, 0.43 day-1 for fresh weight, and 0.39 day-1 for dry weight. In linear regressions, these growth rates were best explained by water temperature. For the populations continuously monitored throughout a year, the nitrogen-to-phosphorus ratio best explained the growth rate of frond numbers. This study yielded a relevant dataset for testing and refining Lemna population models used in chemical risk assessment as well as for managing ecosystems and combating the effects of eutrophication. Integr Environ Assess Manag 2024;20:1625-1638. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Public Health Risks of PFAS-Related Immunotoxicity Are Real.

The discovery of per- and polyfluoroalkyl substances (PFAS) in the environment and humans worldwide has ignited scientific research, government inquiry, and public concern over numerous adverse health effects associated with PFAS exposure. In this review, we discuss the use of PFAS immunotoxicity data in regulatory and clinical decision-making contexts and question whether recent efforts adequately account for PFAS immunotoxicity in public health decision-making. Government and academic reviews confirm the strongest human evidence for PFAS immunotoxicity is reduced antibody production in response to vaccinations, particularly for tetanus and diphtheria. However, recent events, such as the economic analysis supporting the proposed national primary drinking water regulations and clinical monitoring recommendations, indicate a failure to adequately incorporate these data into regulatory and clinical decisions. To be more protective of public health, we recommend using all relevant immunotoxicity data to inform current and future PFAS-related chemical risk assessment and regulation. Biological measures of immune system effects, such as reduced antibody levels in response to vaccination, should be used as valid and informative markers of health outcomes and risks associated with PFAS exposure. Routine toxicity testing should be expanded to include immunotoxicity evaluations in adult and developing organisms. In addition, clinical recommendations for PFAS-exposed individuals and communities should be revisited and strengthened to provide guidance on incorporating immune system monitoring and other actions that can be taken to protect against adverse health outcomes.

Evaluation of models to estimate the bioaccumulation of organic chemicals in earthworms

Modelling approaches to estimate the bioaccumulation of organic chemicals by earthworms are important for improving the realism in risk assessment of chemicals. However, the applicability of existing models is uncertain, partly due to the lack of independent datasets to test them. This study therefore conducted a comprehensive literature review on existing empirical and kinetic models that estimate the bioaccumulation of organic chemicals in earthworms and gathered two independent datasets from published literature to evaluate the predictive performance of these models. The Belfroid et al. (1995a) model is the best-performing empirical model, with 91.2% of earthworm body residue simulations within an order of magnitude of observation. However, this model is limited to the more hydrophobic pesticides and to the earthworm species Eisenia fetida or Eisenia andrei. The kinetic model proposed by Jager et al. (2003b) which out-performs that of Armitage and Gobas (2007), predicted uptake of PCB 153 in the earthworm E. andrei to within a factor of 10. However, the applicability of Jager et al.’s model to other organic compounds and other earthworm species is unknown due to the limited evaluation dataset. The model needs to be parameterised for different chemical, soil, and species types prior to use, which restricts its applicability to risk assessment on a broad scale. Both the empirical and kinetic models leave room for improvement in their ability to reliably predict bioaccumulation in earthworms. Whether they are fit for purpose in environmental risk assessment needs careful consideration on a case by case basis.

A novel method to derive a human safety limit for PFOA by gene expression profiling and modelling.

Perfluorooctanoic acid (PFOA) is a persistent environmental contaminant that can accumulate in the human body due to its long half-life. This substance has been associated with liver, pancreatic, testicular and breast cancers, liver steatosis and endocrine disruption. PFOA is a member of a large group of substances also known as "forever chemicals" and the vast majority of substances of this group lack toxicological data that would enable their effective risk assessment in terms of human health hazards. This study aimed to derive a health-based guidance value for PFOA intake (ng/kg BW/day) from in vitro transcriptomics data. To this end, we developed an in silico workflow comprising five components: (i) sourcing in vitro hepatic transcriptomics concentration-response data; (ii) deriving molecular points of departure using BMDExpress3 and performing pathway analysis using gene set enrichment analysis (GSEA) to identify the most sensitive molecular pathways to PFOA exposure; (iii) estimating freely-dissolved PFOA concentrations in vitro using a mass balance model; (iv) estimating in vivo doses by reverse dosimetry using a PBK model for PFOA as part of a quantitative in vitro to in vivo extrapolation (QIVIVE) algorithm; and (v) calculating a tolerable daily intake (TDI) for PFOA. Fourteen percent of interrogated genes exhibited in vitro concentration-response relationships. GSEA pathway enrichment analysis revealed that "fatty acid metabolism" was the most sensitive pathway to PFOA exposure. In vitro free PFOA concentrations were calculated to be 2.9% of the nominal applied concentrations, and these free concentrations were input into the QIVIVE workflow. Exposure doses for a virtual population of 3,000 individuals were estimated, from which a TDI of 0.15ng/kg BW/day for PFOA was calculated using the benchmark dose modelling software, PROAST. This TDI is comparable to previously published values of 1.16, 0.69, and 0.86ng/kg BW/day by the European Food Safety Authority. In conclusion, this study demonstrates the combined utility of an "omics"-derived molecular point of departure and in silico QIVIVE workflow for setting health-based guidance values in anticipation of the acceptance of in vitro concentration-response molecular measurements in chemical risk assessment.

Innovative analytical methodologies for characterizing chemical exposure with a view to next-generation risk assessment

The chemical burden on the environment and human population is increasing. Consequently, regulatory risk assessment must keep pace to manage, reduce, and prevent adverse impacts on human and environmental health associated with hazardous chemicals. Surveillance of chemicals of known, emerging, or potential future concern, entering the environment-food-human continuum is needed to document the reality of risks posed by chemicals on ecosystem and human health from a one health perspective, feed into early warning systems and support public policies for exposure mitigation provisions and safe and sustainable by design strategies. The use of less-conventional sampling strategies and integration of full-scan, high-resolution mass spectrometry and effect-directed analysis in environmental and human monitoring programmes have the potential to enhance the screening and identification of a wider range of chemicals of known, emerging or potential future concern. Here, we outline the key needs and recommendations identified within the European Partnership for Assessment of Risks from Chemicals (PARC) project for leveraging these innovative methodologies to support the development of next-generation chemical risk assessment.

Intuitive toxicology in the 21st century-Bridging the perspectives of the public and risk assessors in Europe.

Three decades ago, several articles on the subjectivity in chemical risk judgments (i.e., labeled "intuitive toxicology") measured the divide between the public and toxicologists with different backgrounds regarding the validity of predicting health effects based on in vivo studies. Similar divides with impacts on societal discourse and chemical risk assessment practices might exist concerning alternative toxicity testing methods (i.e., in vitro and in silico). However, studies to date have focused either on the public's views of in vivo or stem cell testing or on experts' views of in vivo testing and potential alternatives (i.e., toxicologists and medical students), which do not allow for a direct investigation of potential divides. To fill this knowledge gap, we conducted two online surveys, involving members of the German-speaking public in Switzerland and European human health risk assessors, respectively. This article presents the results of these two surveys regarding the divide in the public's and risk assessors' perspectives on risk assessment based on in vivo, in vitro, and in silico testing. Particularly, the survey with the risk assessors highlights that, beyond scientific and regulatory barriers, alternatives to in vivo testing may encounter individual hurdles, such as higher uncertainty associated with them. Understanding and addressing these hurdles will be crucial to facilitate the integration of new approach methodologies into chemical risk assessment practices as well as a successful transition toward next-generation risk assessment, bringing us closer to a fit-for-purpose and more efficient regulatory landscape.

Comprehensive mapping of the AOP-Wiki database: identifying biological and disease gaps.

Introduction: The Adverse Outcome Pathway (AOP) concept facilitates rapid hazard assessment for human health risks. AOPs are constantly evolving, their number is growing, and they are referenced in the AOP-Wiki database, which is supported by the OECD. Here, we present a study that aims at identifying well-defined biological areas, as well as gaps within the AOP-Wiki for future research needs. It does not intend to provide a systematic and comprehensive summary of the available literature on AOPs but summarizes and maps biological knowledge and diseases represented by the already developed AOPs (with OECD endorsed status or under validation). Methods: Knowledge from the AOP-Wiki database were extracted and prepared for analysis using a multi-step procedure. An automatic mapping of the existing information on AOPs (i.e., genes/proteins and diseases) was performed using bioinformatics tools (i.e., overrepresentation analysis using Gene Ontology and DisGeNET), allowing both the classification of AOPs and the development of AOP networks (AOPN). Results: AOPs related to diseases of the genitourinary system, neoplasms and developmental anomalies are the most frequently investigated on the AOP-Wiki. An evaluation of the three priority cases (i.e., immunotoxicity and non-genotoxic carcinogenesis, endocrine and metabolic disruption, and developmental and adult neurotoxicity) of the EU-funded PARC project (Partnership for the Risk Assessment of Chemicals) are presented. These were used to highlight under- and over-represented adverse outcomes and to identify and prioritize gaps for further research. Discussion: These results contribute to a more comprehensive understanding of the adverse effects associated with the molecular events in AOPs, and aid in refining risk assessment for stressors and mitigation strategies. Moreover, the FAIRness (i.e., data which meets principles of findability, accessibility, interoperability, and reusability (FAIR)) of the AOPs appears to be an important consideration for further development.

Resistance mechanisms of Saccharomyces cerevisiae against silver nanoparticles with different sizes and coatings

To investigate the underlying resistance mechanisms of Saccharomyces cerevisiae against Ag-NPs with different particle sizes and coatings, transcriptome sequencing (RNA-seq) technology was used to characterize the transcriptomes from S. cerevisiae exposed to 20-PVP-Ag, 100-PVP-Ag, 20-CIT-Ag and 100-CIT-Ag, respectively. The steroid biosynthesis was found as a general pathway for Ag-NPs stress responding, in which ERG6 and ERG3 were inhibited and ERG11, ERG25 and ERG5 were significantly up-regulated to resist the stress by supporting the later mutation and resistance and modulate drug efflux indirectly. The resistance mechanism of S. cerevisiae to 20-PVP-Ag seems different from that of 100-PVP-Ag, 20-CIT-Ag and 100-CIT-Ag. Under the 20-PVP-Ag, transmembrane transporter activity, transition metal ion homeostasis and oxidative phosphorylation pathway were main resistance pathways to enhance cell transport processes. While 100-PVP-Ag, 20-CIT-Ag and 100-CIT-Ag mainly impacted RNA binding, structural constituent of ribosome and ribosome pathway which can provide more energy to maintain the number and function of protein in cells. This study reveals the differences in resistance mechanisms of S. cerevisiae to Ag-NPs with different particle sizes and coatings, and explains several main regulatory mechanisms used to respond to silver stress. It will provide theoretical basis for the study of chemical risk assessment.

The new normal chemical landscape: the future of risk assessment toward optimum consumer safety.

The further optimization of consumer safety through risk assessment of chemicals present in food will require adaptability and flexibility to utilize the accelerating developments in safety science and technology. New Approach Methodologies (NAMs) are gaining traction as a systematic approach to support informed decision making in chemical risk assessment. The vision is to be able to predict risk more accurately, rapidly and efficiently. The opportunity exists now to use these approaches which requires a strategy to translate the science into future regulatory implementation. Here we discuss new insights obtained from three recent workshops on how to translate the science into future regulatory implementation. To assist the UK in this endeavor, the Food Standards Agency (FSA) and the scientific advisory committee on chemical toxicity (COT) have been developing a roadmap. In addition, we discuss how these new insights fit into the bigger picture of the new chemical landscape for better consumer safety and the importance of international harmonization.

New approach methodologies (NAMs): identifying and overcoming hurdles to accelerated adoption.

New approach methodologies (NAMs) can deliver improved chemical safety assessment through the provision of more protective and/or relevant models that have a reduced reliance on animals. Despite the widely acknowledged benefits offered by NAMs, there continue to be barriers that prevent or limit their application for decision-making in chemical safety assessment. These include barriers related to real and perceived scientific, technical, legislative and economic issues, as well as cultural and societal obstacles that may relate to inertia, familiarity, and comfort with established methods, and perceptions around regulatory expectations and acceptance. This article focuses on chemical safety science, exposure, hazard, and risk assessment, and explores the nature of these barriers and how they can be overcome to drive the wider exploitation and acceptance of NAMs. Short-, mid- and longer-term goals are outlined that embrace the opportunities provided by NAMs to deliver improved protection of human health and environmental security as part of a new paradigm that incorporates exposure science and a culture that promotes the use of protective toxicological risk assessments.

The role of trust in the use of artificial intelligence for chemical risk assessment

Risk assessment of chemicals is a time-consuming process and needs to be optimized to ensure all chemicals are timely evaluated and regulated. This transition could be stimulated by valuable applications of in silico Artificial Intelligence (AI)/Machine Learning (ML) models. However, implementation of AI/ML models in risk assessment is lagging behind. Most AI/ML models are considered ‘black boxes’ that lack mechanistical explainability, causing risk assessors to have insufficient trust in their predictions.Here, we explore ‘trust’ as an essential factor towards regulatory acceptance of AI/ML models. We provide an overview of the elements of trust, including technical and beyond-technical aspects, and highlight elements that are considered most important to build trust by risk assessors. The results provide recommendations for risk assessors and computational modelers for future development of AI/ML models, including: 1) Keep models simple and interpretable; 2) Offer transparency in the data and data curation; 3) Clearly define and communicate the scope/intended purpose; 4) Define adoption criteria; 5) Make models accessible and user-friendly; 6) Demonstrate the added value in practical settings; and 7) Engage in interdisciplinary settings. These recommendations should ideally be acknowledged in future developments to stimulate trust and acceptance of AI/ML models for regulatory purposes.

Human health risk assessment framework for new water resource recovery-based bio-composite materials.

A new type of bio-composite material is being produced from water-recovered resources such as cellulose fibres from wastewater, calcite from the drinking water softening process, and grass and reed from waterboard sites. These raw materials may be contaminated with pathogens and chemicals such as Escherichia coli, heavy metals, and resin compounds. A novel risk assessment framework is proposed here, addressing human health risks during the production of new bio-composite materials. The developed framework consists of a combination of existing risk assessment methods and is based on three main steps: hazard identification, qualitative risk mapping, and quantitative risk assessment. The HAZOP and Event Tree Analysis methodologies were used for hazard identification and risk mapping stages. Then, human health risks were quantitatively assessed using quantitative chemical risk assessment, evaluating cancer and non-cancer risk, and quantitative microbial risk assessment. The deterministic and the stochastic approaches were performed for this purpose. The contamination of raw materials may pose human health concerns, resulting in cancer risk above the threshold. Microbial risk is also above the safety threshold. Additional analysis would be significant as future research to better assess the microbial risk in biocomposite production. The framework has been effectively used for chemical and microbial risk assessment.

Non-pyrogenicity and biocompatibility of parylene-coated magnetic bead implants.

Clinical grade magnetic bead implants have important applications in interfacing with the human body, providing contactless mechanical attachment or wireless communication through human tissue. We recently developed a new strategy, magnetomicrometry, that uses magnetic bead implants as passive communication devices to wirelessly sense muscle tissue lengths. We manufactured clinical-grade magnetic bead implants and verified their biocompatibility via intramuscular implantation, cytotoxicity, sensitization, and intracutaneous irritation testing. In this work, we test the pyrogenicity of the magnetic bead implants via a lagomorph model, and we test the biocompatibility of the magnetic bead implants via a full chemical characterization and toxicological risk assessment. Further, we test the cleaning, sterilization, and dry time of the devices that are used to deploy these magnetic bead implants. We find that the magnetic bead implants are non-pyrogenic and biocompatible, with the insertion device determined to be safe to clean, sterilize, and dry in a healthcare setting. These results provide confidence for the safe use of these magnetic bead implants in humans.

High-throughput screening of the effects of 90 xenobiotics on the simplified human gut microbiota model (SIHUMIx): a metaproteomic and metabolomic study.

The human gut microbiota is a complex microbial community with critical functions for the host, including the transformation of various chemicals. While effects on microorganisms has been evaluated using single-species models, their functional effects within more complex microbial communities remain unclear. In this study, we investigated the response of a simplified human gut microbiota model (SIHUMIx) cultivated in an in vitro bioreactor system in combination with 96 deep-well plates after exposure to 90 different xenobiotics, comprising 54 plant protection products and 36 food additives and dyes, at environmentally relevant concentrations. We employed metaproteomics and metabolomics to evaluate changes in bacterial abundances, the production of Short Chain Fatty Acids (SCFAs), and the regulation of metabolic pathways. Our findings unveiled significant changes induced by 23 out of 54 plant protection products and 28 out of 36 food additives across all three categories assessed. Notable highlights include azoxystrobin, fluroxypyr, and ethoxyquin causing a substantial reduction (log2FC < -0.5) in the concentrations of the primary SCFAs: acetate, butyrate, and propionate. Several food additives had significant effects on the relative abundances of bacterial species; for example, acid orange 7 and saccharin led to a 75% decrease in Clostridium butyricum, with saccharin causing an additional 2.5-fold increase in E. coli compared to the control. Furthermore, both groups exhibited up- and down-regulation of various pathways, including those related to the metabolism of amino acids such as histidine, valine, leucine, and isoleucine, as well as bacterial secretion systems and energy pathways like starch, sucrose, butanoate, and pyruvate metabolism. This research introduces an efficient in vitro technique that enables high-throughput screening of the structure and function of a simplified and well-defined human gut microbiota model against 90 chemicals using metaproteomics and metabolomics. We believe this approach will be instrumental in characterizing chemical-microbiota interactions especially important for regulatory chemical risk assessments.

A multi-scenario risk assessment strategy applied to mixtures of chemicals of emerging concern in the River Aconcagua basin in Central Chile

Environmental risk assessments strategies that account for the complexity of exposures are needed in order to evaluate the toxic pressure of emerging chemicals, which also provide suggestions for risk mitigation and management, if necessary. Currently, most studies on the co-occurrence and environmental impacts of chemicals of emerging concern (CECs) are conducted in countries of the Global North, leaving massive knowledge gaps in countries of the Global South.In this study, we implement a multi-scenario risk assessment strategy to improve the assessment of both the exposure and hazard components in the chemical risk assessment process. Our strategy incorporates a systematic consideration and weighting of CECs that were not detected, as well as an evaluation of the uncertainties associated with Quantitative Structure-Activity Relationships (QSARs) predictions for chronic ecotoxicity. Furthermore, we present a novel approach to identifying mixture risk drivers. To expand our knowledge beyond well-studied aquatic ecosystems, we applied this multi-scenario strategy to the River Aconcagua basin of Central Chile. The analysis revealed that the concentrations of CECs exceeded acceptable risk thresholds for selected organism groups and the most vulnerable taxonomic groups. Streams flowing through agricultural areas and sites near the river mouth exhibited the highest risks. Notably, the eight risk drivers among the 153 co-occurring chemicals accounted for 66–92 % of the observed risks in the river basin. Six of them are pesticides and pharmaceuticals, chemical classes known for their high biological activity in specific target organisms.

Fish Physiologically Based Toxicokinetic Modeling Approach for In Vitro-In Vivo and Cross-Species Extrapolation of Endocrine-Disrupting Chemicals in Risk Assessment.

High-throughput in vitro assays combined with in vitro-in vivo extrapolation (IVIVE) leverage in vitro responses to predict the corresponding in vivo exposures and thresholds of concern. The integrated approach is also expected to offer the potential for efficient tools to provide estimates of chemical toxicity to various wildlife species instead of animal testing. However, developing fish physiologically based toxicokinetic (PBTK) models for IVIVE in ecological applications is challenging, especially for plausible estimation of an internal effective dose, such as fish equivalent concentration (FEC). Here, a fish PBTK model linked with the IVIVE approach was established, with parameter optimization of chemical unbound fraction, pH-dependent ionization and hepatic clearance, and integration of temperature effect and growth dilution. The fish PBTK-IVIVE approach provides not only a more precise estimation of tissue-specific concentrations but also a reasonable approximation of FEC targeting the estrogenic potency of endocrine-disrupting chemicals. Both predictions were compared with in vivo data and were accurate for most indissociable/dissociable chemicals. Furthermore, the model can help determine cross-species variability and sensitivity among the five fish species. Using the available IVIVE-derived FEC with target pathways is helpful to develop predicted no-effect concentration for chemicals with similar mode of action and support screening-level ecological risk assessment.

Advancing Predictive Risk Assessment of Chemicals via Integrating Machine Learning, Computational Modeling, and Chemical/Nano‐Quantitative Structure‐Activity Relationship Approaches

The escalating use of novel chemicals and nanomaterials (NMs) across diverse sectors underscores the need for advanced risk assessment methods to safeguard human health and the environment. Traditional labor‐intensive approaches have given way to computational methods. This review integrates recent developments in chemical and nano‐quantitative structure‐activity relationship (QSAR) with machine learning and computational modeling, offering a comprehensive predictive assessment of NMs and chemicals. It explores nanodescriptors, their role in predicting toxicity, and the amalgamation of machine learning algorithms with chemical and nano‐QSAR for improved risk assessment accuracy. The article also investigates computational modeling techniques like molecular dynamics simulations, molecular docking, and molecular mechanics/quantum mechanics for predicting physical and chemical properties. By consolidating these approaches, the review advocates for a more accurate and efficient means of assessing risks associated with NMs/chemicals, promoting their safe utilization and minimizing adverse effects on human health and the environment. A valuable resource for researchers and practitioners, informed decision‐making, advancing our understanding of potential risks, is facilitated. Beyond studying systems at various scales, computational modeling integrates data from diverse sources, enhancing risk assessment accuracy and fostering the safe use of NMs/chemicals while minimizing their impact on human health and the environment.

Predicting the Metal Mixture Toxicity with a Toxicokinetic-Toxicodynamic Model Considering the Time-Dependent Adverse Outcome Pathways.

Chemicals mainly exist in ecosystems as mixtures, and understanding and predicting their effects are major challenges in ecotoxicology. While the adverse outcome pathway (AOP) and toxicokinetic-toxicodynamic (TK-TD) models show promise as mechanistic approaches in chemical risk assessment, there is still a lack of methodology to incorporate the AOP into a TK-TD model. Here, we describe a novel approach that integrates the AOP and TK-TD models to predict mixture toxicity using metal mixtures (specifically Cd-Cu) as a case study. We preliminarily constructed an AOP of the metal mixture through temporal transcriptome analysis together with confirmatory bioassays. The AOP revealed that prolonged exposure time activated more key events and adverse outcomes, indicating different modes of action over time. We selected a potential key event as a proxy for damage and used it as a measurable parameter to replace the theoretical parameter (scaled damage) in the TK-TD model. This refined model, which connects molecular responses to organism outcomes, effectively predicts Cd-Cu mixture toxicity over time and can be extended to other metal mixtures and even multicomponent mixtures. Overall, our results contribute to a better understanding of metal mixture toxicity and provide insights for integrating the AOP and TK-TD models to improve risk assessment for chemical mixtures.